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“A New Periodic Table of Machine Learning: Unlocking AI Discovery and Innovation”

After uncovering a unifying algorithm that links more than 20 common machine-learning approaches, researchers organized them into a ‘periodic table of machine learning’ that can help scientists combine elements of different methods to improve algorithms or create new ones.

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MIT researchers have created a groundbreaking periodic table that reveals how more than 20 classical machine-learning algorithms are connected. This innovative framework sheds light on how scientists can fuse strategies from different methods to improve existing AI models or come up with new ones.

The researchers used their framework to combine elements of two different algorithms to create a new image-classification algorithm that performed 8 percent better than current state-of-the-art approaches. This breakthrough demonstrates the potential of the periodic table to unlock AI discovery and innovation.

The periodic table stems from one key idea: All these algorithms learn a specific kind of relationship between data points. While each algorithm may accomplish that in a slightly different way, the core mathematics behind each approach is the same. Building on these insights, the researchers identified a unifying equation that underlies many classical AI algorithms.

They used this equation to reframe popular methods and arrange them into a table, categorizing each based on the approximate relationships it learns. Just like the periodic table of chemical elements, which initially contained blank squares that were later filled in by scientists, the periodic table of machine learning also has empty spaces.

These spaces predict where algorithms should exist, but which haven’t been discovered yet. The researchers filled one gap by borrowing ideas from a machine-learning technique called contrastive learning and applying them to image clustering. This resulted in a new algorithm that could classify unlabeled images 8 percent better than another state-of-the-art approach.

The flexible periodic table allows researchers to add new rows and columns to represent additional types of datapoint connections. Ultimately, having I-Con as a guide could help machine learning scientists think outside the box, encouraging them to combine ideas in ways they wouldn’t necessarily have thought of otherwise.

This research was funded, in part, by the Air Force Artificial Intelligence Accelerator, the National Science Foundation AI Institute for Artificial Intelligence and Fundamental Interactions, and Quanta Computer. The researchers’ work will be presented at the International Conference on Learning Representations.

Alternative Fuels

“Revolutionizing Energy Storage: Scientists Break World Record with Lithium-Ion Conductors”

A team partially replaced lithium in a lithium antimonide compound with the metal scandium. This creates specific gaps, so-called vacancies, in the crystal lattice of the conductor material. These gaps help the lithium ions to move more easily and faster, resulting in a new world record for ion conductivity.

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The pursuit of efficient energy storage has led scientists to explore novel materials for solid-state batteries. Researchers at TUM and TUMint.Energy Research have taken a groundbreaking step forward by developing a new material that conducts lithium ions more than 30% faster than any previously known substance. This breakthrough, achieved through the creation of a lithium-antimonide compound with scandium, has far-reaching implications for the future of energy storage.

The team, led by Prof. Thomas F. Fässler from the Chair of Inorganic Chemistry with a Focus on Novel Materials, discovered that by partially replacing lithium in a lithium antimonide compound with the metal scandium, they could create specific gaps or vacancies in the crystal lattice of the conductor material. These gaps allowed the lithium ions to move more easily and faster, resulting in an unprecedented level of ion conductivity.

To validate this result, the team collaborated with the Chair of Technical Electrochemistry under Prof. Hubert Gasteiger at TUM. Co-author Tobias Kutsch, who conducted the validation tests, noted that the material also conducts electricity, presenting a special challenge for measurement methods.

Prof. Fässler sees great potential in the new material: “Our result currently represents a significant advance in basic research. By incorporating small amounts of scandium, we have uncovered a new principle that could prove to be a blueprint for other elemental combinations.” The team is optimistic about the practical applications of this discovery, particularly as additives in electrodes.

In addition to its faster conductivity, the material also offers thermal stability and can be produced using well-established chemical methods. The researchers believe that their combination of lithium-antimony could have broader implications for enhancing conductivity in a wide range of other materials.

The team has even discovered an entirely new class of substances through their work, as first author Jingwen Jiang emphasizes: “Our combination consists of lithium-antimony, but the same concept can easily be applied to lithium-phosphorus systems. While the previous record holder relied on lithium-sulphur and required five additional elements for optimization, we only need Scandium as an additional component.”

This breakthrough has the potential to revolutionize energy storage, making it more efficient and sustainable for a wide range of applications. The researchers’ enthusiasm is evident in their pursuit of further testing and validation, with the goal of integrating this new material into practical battery cells.

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Civil Engineering

The Sinking Cities of America: A Study Reveals Widespread Land Movement Across 28 Major U.S. Metropolises

A new study of the 28 most populous U.S. cities finds that all are sinking to one degree or another. The cities include not just those on the coasts, where relative sea level is a concern, but many in the interior. Furthermore, using newly granular data, the study finds that some cities are sinking at different rates in different spots, or sinking in some places and rising in others, potentially introducing stresses that could affect buildings and other infrastructure.

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The study, published in Nature Cities, reveals that all 28 most populous U.S. cities are experiencing some degree of land movement, with the majority sinking at varying rates due to a combination of factors including groundwater extraction, climate change, and human activities such as construction and urbanization.

Lead author Leonard Ohenhen, a postdoctoral researcher at Columbia Climate School’s Lamont-Doherty Earth Observatory, notes that as cities continue to grow, subsidence can become more pronounced, producing stresses on infrastructure that may exceed safety limits. “We will see more cities expand into subsiding regions,” he says.

The study uses satellite data to map land movements in the 28 cities, including Houston, which is experiencing some of the most rapid sinking, with over 40% of its area subsiding more than 5 millimeters per year. Other Texas cities, Fort Worth and Dallas, are also among the fastest-sinking, while areas around New York’s LaGuardia Airport and parts of Las Vegas, Washington, D.C., and San Francisco are experiencing localized fast-sinking zones.

Researchers found that groundwater removal for human use was responsible for 80% of overall sinkage, with compaction below ground level causing subsidence at the surface. Climate-induced droughts in some areas will likely worsen subsidence in the future, says Ohenhen.

The study also reveals that natural forces are at work in some areas, such as the weight of ancient ice sheets that once covered much of interior North America. Even today, some cities like New York, Indianapolis, Nashville, Philadelphia, Denver, Chicago, and Portland are still subsiding due to these bulges, with rates ranging from 1 to 3 millimeters per year.

The researchers emphasize that continued population growth and water usage will likely exacerbate subsidence in the future. They recommend that cities focus on solutions such as land raising, enhanced drainage systems, and green infrastructure to mitigate flooding, and retrofitting existing structures to address tilting hazards.

Ohenhen concludes, “We have to move to solutions.” The study was coauthored by researchers from various institutions and provides a valuable resource for policymakers and urban planners to address the challenges posed by subsidence in major American cities.

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Artificial Intelligence

The Hidden Barrier to Advanced Robotic Touch

Researchers argue that the problem that has been lurking in the margins of many papers about touch sensors lies in the robotic skin itself.

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The development of advanced robotic touch has been hindered by a seemingly innocuous yet critical issue – the insulating layer in robotic skin. Researchers at Northwestern University and Tel Aviv University have successfully overcome this barrier, paving the way for low-cost solutions that enable robots to mimic human touch.

In their study, the researchers observed that inexpensive silicon rubber composites used to make robotic skin host an insulating layer on both top and bottom surfaces. This prevents direct electrical contact between the sensing polymer and the monitoring surface electrodes, making accurate and repeatable measurements impossible. By eliminating this error, cheap robotic skins can now allow robots to sense an object’s curves and edges, essential for proper grasping.

The research team, consisting of electrical engineers and polymer materials scientists, shed light on this problem in a paper published in Advanced Electronic Materials. The study highlights the importance of validating electrical contacts, which might unknowingly obscure device performance.

“A lot of scientists misunderstand their sensor response because they lump together the behavior of the contacts with the behavior of the sensor material, resulting in inconsistent data,” said Matthew Grayson, professor of electrical and computer engineering at Northwestern’s McCormick School of Engineering. “Our work identifies the exact problem, quantifies its extent both microscopically and electrically, and gives a clear step-by-step trouble-shooting manual to fix the problem.”

The researchers detected that adding electrically conducting fillers like carbon nanotubes to rubber composites creates an ideal candidate for touch sensors. However, this material needs electrical signals, which are blocked by the insulating layer. By sanding down the ultrathin insulation layer, the team achieved a stronger electrical contact and calibrated the thickness of the insulating layer.

The collaboration between Northwestern University and Tel Aviv University is essential in addressing the “contact preparation” challenge. The researchers relied on each other’s expertise to prepare materials and study their properties, leading to consistent results across various variables.

As awareness spreads among researchers about the issue of reproducibility in touch sensing literature, new publications can be more rigorously relied upon to advance the field with new capabilities. The research was supported by various organizations, including the U.S. National Science Foundation, Northwestern University, and Tel Aviv University through the Center for Nanoscience & Nanotechnology.

The breakthrough has significant implications for robotics development, enabling robots to sense and interact with their environment more effectively. By overcoming this critical barrier, researchers have opened up new possibilities for advanced robotic touch, paving the way for future innovations in robotics and beyond.

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